Learning to Detect Symbolic Failure: Machine Learning and the Limits of Black-Scholes

arXiv:2609.27764 · cs.LG, cs.CE · Submitted 2026-08-24 · Read on arXiv

cs.LG, cs.CE

Submitted: 2026-08-24

Updated: 2026-08-24

Terminology

• Accuracy — 13× in this paper · explained in 1 episode
• Embeddings — 10× in this paper · explained in 2 episodes
• Neural Network — 10× in this paper
• Abstraction — 9× in this paper · explained in 1 episode
• Consistency — 4× in this paper · explained in 3 episodes
• Latent Space — 3× in this paper · explained in 7 episodes
• Robustness — 3× in this paper · explained in 5 episodes
• Diffusion Model — 2× in this paper · explained in 8 episodes
• Diffusion Models — 2× in this paper · explained in 6 episodes
• alpha — 2× in this paper · explained in 1 episode
• Clustering — 1× in this paper · explained in 2 episodes
• Core — 1× in this paper · explained in 2 episodes
• Feature Engineering — 1× in this paper · explained in 3 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Interpretability — 1× in this paper · explained in 15 episodes
• Yet the Black-Scholes — 1× in this paper

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